Biology subjects

Sassi, F.

Publications and source records attributed to Sassi, F..

6 recordsLinked to original sources

bioRxiv2025

On-target mutations confer resistance to WRN helicase inhibitors in Microsatellite Unstable Cancer Cells.

Werner helicase inhibitors (WRNi) are in clinical development for microsatellite-unstable (MSI) tumors with defective DNA mismatch repair. Here, we investigate how cancer cell evolution shapes response to WRN inhibition and informs potential resistance mechanisms. Genome-wide CRISPR screens combined with WRN knockout did not identify bypass mechanisms, underscoring WRNs essential, non-redundant function in MSI cells. Pharmacogenomic screens identified modulators of WRNi sensitivity, including SMARCAL1, which links it to WRN-MSI synthetic lethality. Semi-saturation mutagenesis of WRN and prolonged drug treatment identified on-target WRN mutations driving acquired resistance to multiple WRNi in vitro and in vivo, which was mitigated by combination with standard chemotherapies. Some resistance mutations conferred broad cross-resistance, whereas others preserved sensitivity to alternative clinical-grade WRNi with distinct mechanism of action. Our findings could inform clinical trial design by suggesting the feasibility of real-time tracking of emerging resistance and enabling early therapeutic adaptations. SignificanceWe present the first exploration of how MSI cancer cells evolve under the selective pressure of WRN helicase inhibition, providing a framework for understanding adaptive responses to this newly identified synthetic-lethal dependency. This study identifies on-target WRN mutations as key drivers of resistance in MSI cancers, supporting the use of combination strategies with other standard-of-care treatments to prevent resistance. It highlights how mutation tracking can guide therapeutic switching to clinically available WRN inhibitors with distinct mechanisms of action, thereby refining clinical development and potentially improving biomarker-informed patient outcomes.

cancer biology↗

bioRxiv2024

Heterogeneity and evolution of DNA mutation rates in microsatellite stable colorectal cancer

DNA sequence mutability in tumors with chromosomal instability is conventionally believed to remain uniform, constant, and low, based on the assumption that further mutational accrual in a context of marked aneuploidy is evolutionarily disadvantageous. However, this concept lacks robust experimental verification. We adapted the principles of mutation accumulation experiments, traditionally performed in lower organisms, to clonal populations of patient-derived tumoroids and empirically measured the spontaneous rates of accumulation of new DNA sequence variations in seven chromosomally unstable, microsatellite stable colorectal cancers (CRCs) and one microsatellite unstable CRC. Our findings revealed heterogeneous mutation rates (MRs) across different tumors, with variations in magnitude within microsatellite stable tumors as prominent as those distinguishing them from microsatellite unstable tumors. Moreover, comparative assessment of microsatellite stable primary tumors and matched synchronous metastases consistently documented a pattern of MR intensification during tumor progression. Therefore, wide-range diversity and progression-associated evolvability of DNA sequence mutational instability emerge as unforeseen hallmarks of microsatellite stable CRC, complementing karyotype alterations as selectable traits to increase genetic variation. One sentence summaryTumors with chromosomal instability accrue DNA sequence mutations at highly variable rates, which increase during metastatic progression.

cancer biology↗

bioRxiv2023

XENTURION, a multidimensional resource of xenografts and tumoroids from metastatic colorectal cancer patients for population-level translational oncology

The breadth and depth at which cancer models are interrogated contribute to successful translation of drug discovery efforts to the clinic. In colorectal cancer (CRC), model availability is limited by a dearth of large-scale collections of patient-derived xenografts (PDXs) and paired tumoroids from metastatic disease, the setting where experimental therapies are typically tested. XENTURION is a unique open-science resource that combines a platform of 129 PDX models and a sister platform of 129 matched PDX-derived tumoroids (PDXTs) from patients with metastatic CRC, with accompanying multidimensional molecular and therapeutic characterization. A PDXT-based population trial with the anti-EGFR antibody cetuximab revealed variable sensitivities that were consistent with clinical response biomarkers, mirrored tumor growth changes in matched PDXs, and recapitulated the outcome of EGFR genetic deletion. Adaptive signals upregulated by EGFR blockade were computationally and functionally prioritized, and inhibition of top candidates increased the magnitude of response to cetuximab. These findings illustrate the probative value and accuracy of large ex vivo and in vivo living biobanks, highlight the importance of cross-platform and cross-methodology systematic validation, and offer avenues for molecularly informed preclinical research.

cancer biology↗

bioRxiv2022

CONNECTOR, fitting and clustering of longitudinal data to reveal a new risk stratification system.

The transition from the evaluation of a single time point to the examination of the entire dynamic evolution of a system is possible only in the presence of the proper framework. The strong variability of dynamic evolution makes the definition of an explanatory procedure for data fitting and data clustering challenging. Here we present CONNECTOR, a data-driven framework able to analyze and inspect longitudinal data in a straightforward and revealing way. When used to analyze tumor growth kinetics over time in 1599 patient-derived xenograft (PDX) growth curves from ovarian and colorectal cancers, CONNECTOR allowed the aggregation of time-series data through an unsupervised approach in informative clusters. Through the lens of a new perspective of mechanism interpretation, CONNECTOR shed light onto novel model aggregations and identified unanticipated molecular associations with response to clinically approved therapies.

bioinformatics↗

bioRxiv2020

GREATER EMPATHIC ABILITIES AND THEIR CORELATION WITH RESTING STATE BRAIN CONNECTIVITY IN PSYCHOTHERAPISTS COMPARED TO NON-PSYCHOTHERAPISTS

Psychotherapists constantly regulate their own perspective and emotions to better understand the "others" state. We compared 52 psychotherapists with 92 non-psychotherapists to characterized psychometric constructs like, Fantasy (FS) and Perspective Taking (PT), and the emotion regulation strategy of Expressive Suppression (ES), which hampers the empathic response. Psychotherapists showed greater FS, PT and lower ES scores. In a subsample (36, 18 ea.), we did a functional connectivity (FC) study. Psychotherapists showed greater FC between the left anterior insula and the dorsomedial prefrontal cortex; and less connectivity between rostral anterior cingulate cortex and the orbito prefrontal cortex. Both associations correlated with the PT scores and suggest a cognitive regulatory effect related to the empathic response. Considering, that the psychometric differences between groups were in the cognitive domain and that the FC associations are related to cognitive processes, these results suggest that psychotherapists have a greater cognitive regulation over their empathic response.

neuroscience↗

bioRxiv2019

Effects of body mass index on relationship status, social contact, and socioeconomic position: Mendelian Randomization study in UK Biobank

ObjectiveTo assess whether body mass index (BMI) has a causal effect on social and socioeconomic factors, including whether both high and low BMI can be detrimental.\n\nDesignMendelian Randomization, using genetic variants for BMI to obtain unconfounded estimates, and non-linear Mendelian Randomization.\n\nSettingUK Biobank.\n\nParticipants378,244 men and women of European ancestry, mean age 57 (SD 8 years).\n\nMain outcome measuresTownsend deprivation index, income, age completed full time education, degree level education, job class, employment status, cohabiting relationship status, participation in leisure and social activities, visits from friends and family, and having someone to confide in.\n\nResultsHigher BMI was causally associated with higher deprivation, lower income, fewer years of education, lower odds of degree-level education and skilled employment. For example, a 1 SD higher genetically-determined BMI (4.8kg/m2 in UK Biobank) was associated with {pound}1,660 less income per annum [95%CI: {pound}950, {pound}2,380]. Non-linear Mendelian Randomization provided evidence that both low BMI (bottom decile, <22kg/m2) and high BMI (top seven deciles, >24.6kg/m2) can increase deprivation and reduce income. In men only, higher BMI was related to lower participation in leisure and social activities. There was no evidence of causal effects of BMI on visits from friends and family or in having someone to confide in. Non-linear Mendelian Randomization analysis showed that low BMI (bottom three deciles, <23.5kg/m2) reduces the odds of cohabiting with a partner or spouse for men, whereas high BMI (top two deciles, >30.7kg/m2) reduces the odds of cohabitation with a partner or spouse for women.\n\nConclusionsBMI affects social and socioeconomic outcomes, with both high and low BMI being detrimental for some measures of SEP. This suggests that in addition to health benefits, maintaining healthy ranges of BMI across the population could have benefits both for individuals and society.

epidemiology↗